Measuring Community Resilience to Coastal Hazards along the Northern Gulf of Mexico.

The abundant research examining aspects of social-ecological resilience, vulnerability, and hazards and risk assessment has yielded insights into these concepts and suggested the importance of quantifying them. Quantifying resilience is complicated by several factors including the varying definitions of the term applied in the research, difficulties involved in selecting and aggregating indicators of resilience, and the lack of empirical validation for the indices derived. This paper applies a new model, called the resilience inference measurement (RIM) model, to quantify resilience to climate-related hazards for 52 U.S. counties along the northern Gulf of Mexico. The RIM model uses three elements (exposure, damage, and recovery indicators) to denote two relationships (vulnerability and adaptability), and employs both K-means clustering and discriminant analysis to derive the resilience rankings, thus enabling validation and inference. The results yielded a classification accuracy of 94.2% with 28 predictor variables. The approach is theoretically sound and can be applied to derive resilience indices for other study areas at different spatial and temporal scales.

Influences on Adaptive Planning to Reduce Flood Risks among Parishes in South Louisiana.

Residents of south Louisiana face a range of increasing, climate-related flood exposure risks that could be reduced through local floodplain management and hazard mitigation planning. A major incentive for community planning to reduce exposure to flood risks is offered by the Community Rating System (CRS) of the National Flood Insurance Program (NFIP). The NFIP encourages local collective action by offering reduced flood insurance premiums for individual policy holders of communities where suggested risk-reducing measures have been implemented. This preliminary analysis examines the extent to which parishes (counties) in southern Louisiana have implemented the suggested policy actions and identifies key factors that account for variation in the implementation of the measures. More measures implemented results in higher CRS scores. Potential influences on scores include socioeconomic attributes of residents, government capacity, average elevation and past flood events. The results of multiple regression analysis indicate that higher CRS scores are associated most closely with higher median housing values. Furthermore, higher scores are found in parishes with more local municipalities that participate in the CRS program. The number of floods in the last five years and the revenue base of the parish does not appear to influence CRS scores. The results shed light on the conditions under which local adaptive planning to mitigate increasing flood risks is more likely to be implemented and offer insights for program administrators, researchers and community stakeholders.

Co-evolution of wetland landscapes, flooding, and human settlement in the Mississippi River Delta Plain.

River deltas all over the world are sinking beneath sea-level rise, causing significant threats to natural and social systems. This is due to the combined effects of anthropogenic changes to sediment supply and river flow, subsidence, and sea-level rise, posing an immediate threat to the 500-1,000 million residents, many in megacities that live on deltaic coasts. The Mississippi River Deltaic Plain (MRDP) provides examples for many of the functions and feedbacks, regarding how human river management has impacted source-sink processes in coastal deltaic basins, resulting in human settlements more at risk to coastal storms. The survival of human settlement on the MRDP is arguably coupled to a shifting mass balance between a deltaic landscape occupied by either land built by the Mississippi River or water occupied by the Gulf of Mexico. We developed an approach to compare 50 % L:W isopleths (L:W is ratio of land to water) across the Atchafalaya and Terrebonne Basins to test landscape behavior over the last six decades to measure delta instability in coastal deltaic basins as a function of reduced sediment supply from river flooding. The Atchafalaya Basin, with continued sediment delivery, compared to Terrebonne Basin, with reduced river inputs, allow us to test assumptions of how coastal deltaic basins respond to river management over the last 75 years by analyzing landward migration rate of 50 % L:W isopleths between 1932 and 2010. The average landward migration for Terrebonne Basin was nearly 17,000 m (17 km) compared to only 22 m in Atchafalaya Basin over the last 78 years (p < 0.001), resulting in migration rates of 218 m/year (0.22 km/year) and <0.5 m/year, respectively. In addition, freshwater vegetation expanded in Atchafalaya Basin since 1949 compared to migration of intermediate and brackish marshes landward in the Terrebonne Basin. Changes in salt marsh vegetation patterns were very distinct in these two basins with gain of 25 % in the Terrebonne Basin compared to 90 % decrease in the Atchafalaya Basin since 1949. These shifts in vegetation types as L:W ratio decreases with reduced sediment input and increase in salinity also coincide with an increase in wind fetch in Terrebonne Bay. In the upper Terrebonne Bay, where the largest landward migration of the 50 % L:W ratio isopleth occurred, we estimate that the wave power has increased by 50-100 % from 1932 to 2010, as the bathymetric and topographic conditions changed, and increase in maximum storm-surge height also increased owing to the landward migration of the L:W ratio isopleth. We argue that this balance of land relative to water in this delta provides a much clearer understanding of increased flood risk from tropical cyclones rather than just estimates of areal land loss. We describe how coastal deltaic basins of the MRDP can be used as experimental landscapes to provide insights into how varying degrees of sediment delivery to coastal deltaic floodplains change flooding risks of a sinking delta using landward migrations of 50 % L:W isopleths. The nonlinear response of migrating L:W isopleths as wind fetch increases is a critical feedback effect that should influence human river-management decisions in deltaic coast. Changes in land area alone do not capture how corresponding landscape degradation and increased water area can lead to exponential increase in flood risk to human populations in low-lying coastal regions. Reduced land formation in coastal deltaic basins (measured by changes in the land:water ratio) can contribute significantly to increasing flood risks by removing the negative feedback of wetlands on wave and storm-surge that occur during extreme weather events. Increased flood risks will promote population migration as human risks associated with living in a deltaic landscape increase, as land is submerged and coastal inundation threats rise. These system linkages in dynamic deltaic coasts define a balance of river management and human settlement dependent on a certain level of land area within coastal deltaic basins (L).

Modeling land use and land cover changes in a vulnerable coastal region using artificial neural networks and cellular automata.

As one of the most vulnerable coasts in the continental USA, the Lower Mississippi River Basin (LMRB) region has endured numerous hazards over the past decades. The sustainability of this region has drawn great attention from the international, national, and local communities, wanting to understand how the region as a system develops under intense interplay between the natural and human factors. A major problem in this deltaic region is significant land loss over the years due to a combination of natural and human factors. The main scientific and management questions are what factors contribute to the land use land cover (LULC) changes in this region, can we model the changes, and how would the LULC look like in the future given the current factors? This study analyzed the LULC changes of the region between 1996 and 2006 by utilizing an artificial neural network (ANN) to derive the LULC change rules from 15 human and natural variables. The rules were then used to simulate future scenarios in a cellular automation model. A stochastic element was added in the model to represent factors that were not included in the current model. The analysis was conducted for two sub-regions in the study area for comparison. The results show that the derived ANN models could simulate the LULC changes with a high degree of accuracy (above 92 % on average). A total loss of 263 km(2) in wetlands from 2006 to 2016 was projected, whereas the trend of forest loss will cease. These scenarios provide useful information to decision makers for better planning and management of the region.

Applying a community resilience framework to examine household emergency planning and exposure-reducing behavior among residents of Louisiana's industrial corridor.

Residents facing environmental hazards can take steps to reduce their exposure risks, and these actions may be considered adaptations that can enhance the overall resilience of communities. Applying concepts from social-ecological resilience theory, the authors examine emergency planning and exposure-reducing behaviors among residents of the upper Industrial Corridor of Louisiana and explore the extent to which the behaviors are associated with key theoretical influences on community resilience: exposure, vulnerability, and the "adaptive capacity" of residents. The behaviors of interest are adoption of a household emergency plan in the case of acute exposure events (like chemical spills), and limiting outdoor activities in response to Air Quality Index reports, thus potentially reducing chronic exposure risks. Statistical analyses indicate that adaptive behaviors are associated both with greater exposure to hazards and confidence in one's knowledge and ability to reduce exposure risks. Thus, the study yields evidence that "adaptive capacity" is particularly relevant to understanding and encouraging household emergency planning. Residents who believe that they are well-informed about risk-reducing strategies, regardless of education or income, were found to be more likely to have adopted these measures. Evidence that knowledge and confidence levels are linked to adaptive behaviors is good news for those working in public education and outreach programs, as these are attitudes and skills that can be nurtured. While factors associated with exposure and vulnerability to hazards are difficult to change, knowledge of risk-reducing strategies and confidence in one's abilities to reduce exposure risks can be improved through well-designed public education efforts.

Predictors of business return in New Orleans after Hurricane Katrina.

We analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of businesses in New Orleans was conducted in October 2007, 26 months after Hurricane Katrina. The data were analyzed using a modified spatial probit regression model to evaluate the importance of each predictor variable through time. The results suggest that the two most important reopening predictors throughout all time periods were the flood depth at the business location and business size as represented by its wages in a logarithmic form. Flood depth was a significant negative predictor and had the largest marginal effects on the reopening probabilities. Smaller businesses had lower reopening probabilities than larger ones. However, the nonlinear response of business size to the reopening probability suggests that recovery aid would be most effective for smaller businesses than for larger ones. The spatial spillovers effect was a significant positive predictor but only for the first nine months. The findings show clearly that flood protection is the overarching issue for New Orleans. A flood protection plan that reduces the vulnerability and length of flooding would be the first and foremost step to mitigate the negative effects from climate-related hazards and enable speedy recovery. The findings cast doubt on the current coastal protection efforts and add to the current debate of whether coastal Louisiana will be sustainable or too costly to protect from further land loss and flooding given the threat of sea-level rise. Finally, a plan to help small businesses to return would also be an effective strategy for recovery, and the temporal window of opportunity that generates the greatest impacts would be the first 6∼9 months after the disaster.

Achievement of Climate Planning Objectives among U.S. Member Cities of the International Council for Local Environmental Initiatives (ICLEI).

In an effort to address climate change, many cities have joined the International Council for Local Environmental Initiatives (ICLEI) whose members commit to work toward five specific program objectives designed to reduce greenhouse gas emissions. This study examines the extent to which 257 member cities in the US have been successful in achieving these program milestones and identifies factors that may explain variation in the performance of member cities. Potential influences on milestone attainment include socioeconomic, political and ideological characteristics of residents, length of ICLEI membership, existence of other climate programs within the state, and local environmental pressures. Multiple regression results indicate that length of membership is the strongest predictor of milestone attainment, regardless of local socioeconomic conditions, ideological and political orientations of residents, or other climate-related initiatives within the state. This finding supports the general effectiveness of ICLEI's network organizational model and its outreach and education efforts. However, member cities facing more "climate stress", including higher levels of hazardous air pollutants (HAP's) and greater automobile use among residents are making slower progress. The findings yield insight into the conditions under which cities engaged in climate planning are more likely to succeed in reducing local greenhouse gas emissions-relevant information for planners, community stakeholders and administrators of organizations like ICLEI.

Measuring Capacity for Resilience among Coastal Counties of the US Northern Gulf of Mexico Region.

Many have voiced concern about the long-term survival of coastal communities in the face of increasingly intense storms and sea level rise. In this study we select indicators of key theoretical concepts from the social-ecological resilience literature, aggregate those indicators into a resilience-capacity index, and calculate an index score for each of the 52 coastal counties of Louisiana, Texas, Mississippi, Alabama and Florida. Building upon Cutter's Social Vulnerability Index work [1], we use Factor Analysis to combine 43 variables measuring demographics, social capital, economic resources, local government actions, and environmental conditions within the counties. Then, we map the counties' scores to show the spatial distribution of resilience capacities. The counties identified as having the highest resilience capacities include the suburban areas near New Orleans, Louisiana and Tampa, Florida, and the growing beach-tourist communities of Alabama and central Florida. Also, we examine whether those counties more active in oil and gas development and production, part of the region's "energy coast", have greater capacity for resilience than other counties in the region. Correlation analyses between the resilience-capacity index scores and two measures of oil and gas industry activity (total employment and number of business establishments within five industry categories) yielded no statistically significant associations. By aggregating a range of important contextual variables into a single index, the study demonstrates a useful approach for the more systematic examination and comparison of exposure, vulnerability and capacity for resilience among coastal communities.

A new method for estimating carbon dioxide emissions from transportation at fine spatial scales.

Detailed estimates of carbon dioxide (CO2) emissions at fine spatial scales are useful to both modelers and decision makers who are faced with the problem of global warming and climate change. Globally, transport related emissions of carbon dioxide are growing. This letter presents a new method based on the volume-preserving principle in the areal interpolation literature to disaggregate transportation-related CO2 emission estimates from the county-level scale to a 1 km2 grid scale. The proposed volume-preserving interpolation (VPI) method, together with the distance-decay principle, were used to derive emission weights for each grid based on its proximity to highways, roads, railroads, waterways, and airports. The total CO2 emission value summed from the grids within a county is made to be equal to the original county-level estimate, thus enforcing the volume-preserving property. The method was applied to downscale the transportation-related CO2 emission values by county (i.e. parish) for the state of Louisiana into 1 km2 grids. The results reveal a more realistic spatial pattern of CO2 emission from transportation, which can be used to identify the emission 'hot spots'. Of the four highest transportation-related CO2 emission hotspots in Louisiana, high-emission grids literally covered the entire East Baton Rouge Parish and Orleans Parish, whereas CO2 emission in Jefferson Parish (New Orleans suburb) and Caddo Parish (city of Shreveport) were more unevenly distributed. We argue that the new method is sound in principle, flexible in practice, and the resultant estimates are more accurate than previous gridding approaches.

Business return in New Orleans: decision making amid post-Katrina uncertainty.

BACKGROUND: Empirical observations on how businesses respond after a major catastrophe are rare, especially for a catastrophe as great as Hurricane Katrina, which hit New Orleans, Louisiana on August 29, 2005. We analyzed repeated telephone surveys of New Orleans businesses conducted in December 2005, June 2006, and October 2007 to understand factors that influenced decisions to re-open amid post-disaster uncertainty. METHODOLOGY/PRINCIPAL FINDINGS: Businesses in the group of professional, scientific, and technical services reopened the fastest in the near term, but differences in the rate of reopening for businesses stratified by type became indistinguishable in the longer term (around two years later). A reopening rate of 65% was found for all businesses by October 2007. Discriminant analysis showed significant differences in responses reflecting their attitudes about important factors between businesses that reopened and those that did not. Businesses that remained closed at the time of our third survey (two years after Katrina) ranked levee protection as the top concern immediately after Katrina, but damage to their premises and financing became major concerns in subsequent months reflected in the later surveys. For businesses that had opened (at the time of our third survey), infrastructure protection including levee, utility, and communications were the main concerns mentioned in surveys up to the third survey, when the issue of crime became their top concern. CONCLUSIONS/SIGNIFICANCE: These findings underscore the need to have public policy and emergency plans in place prior to the actual disaster, such as infrastructure protection, so that the policy can be applied in a timely manner before business decisions to return or close are made. Our survey results, which include responses from both open and closed businesses, overcome the "survivorship bias" problem and provide empirical observations that should be useful to improve micro-level spatial economic modeling of factors that influence business return decisions.

Socioeconomic inequality of cancer mortality in the United States: a spatial data mining approach.

BACKGROUND: The objective of this study was to demonstrate the use of an association rule mining approach to discover associations between selected socioeconomic variables and the four most leading causes of cancer mortality in the United States. An association rule mining algorithm was applied to extract associations between the 1988-1992 cancer mortality rates for colorectal, lung, breast, and prostate cancers defined at the Health Service Area level and selected socioeconomic variables from the 1990 United States census. Geographic information system technology was used to integrate these data which were defined at different spatial resolutions, and to visualize and analyze the results from the association rule mining process. RESULTS: Health Service Areas with high rates of low education, high unemployment, and low paying jobs were found to associate with higher rates of cancer mortality. CONCLUSION: Association rule mining with geographic information technology helps reveal the spatial patterns of socioeconomic inequality in cancer mortality in the United States and identify regions that need further attention.